Cognitive memory for semantic agents in Robotic interaction

Abstract

Since 1960, lots of AI researchers work on intelligent and reactive architectures able to manage multiple events and act in the environment. This issue is also part of Robotics domain. A decision process must be implemented in the robot brain to accomplish the multimodal interaction with human in human environment. In this article, we present a semantic agents architecture giving the robot the ability to well understand what is happening and thus provide more robust responses. We will describe here our agent component. Intelligence and knowledge about objects in the environment is stored in two ontologies linked to a reasoner, the inference engine. To share and exchange information, an event knowledge representation language is used by semantic agents. This architecture brings other advantages: pervasive, cooperating, redundant, automatically adaptable and interoperable. It is independent of platforms.